1,721,005 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Understanding and managing the impacts of climate change in a complex environmental system: The effects of increasing precipitation and land use change on streamflow
No full textIncreased variability in the hydrologic cycle, including more extreme rainstorms and flood events, is anticipated as a result of global climate change. These variations may be exacerbated by alterations within watershed boundaries, such as land use change. In order to determine the relative impacts of precipitation and land use change on streamflow, spatial and temporal trends in precipitation and streamflow were examined for small watersheds throughout the United States, with particular emphasis on Midwestern regional and local changes. In the 160 watersheds selected for analysis, only nineteen sites had increasing trends in both precipitation and streamflow and increasing trends in peak streamflow were more than twice as prevalent as increasing trends in peak precipitation, indicating that many peak streamflow increases were not driven by changes in peak precipitation events. Seasonal analysis of peak daily precipitation and streamflow data in the Midwest indicated that half of all study sites had significant (α = 0.05) increasing trends in peak fall streamflow and nearly 40% of sites had significant trends in peak daily precipitation. This high number of sites with increases greatly overshadowed the number of sites with significant changes occurring in other seasons, and were significantly impacted by the level of watershed imperviousness; watersheds with impervious levels exceeding sixteen percent had greater increases in peak fall streamflow. Additional analysis of precipitation records in the Midwest indicated that precipitation statistics commonly used in engineering design are outdated, with increases in design storm event depths becoming greater over time, even though trends in peak precipitation events are not significantly increasing. Such changes in precipitation and streamflow require adaptive water resource plans to be in place for communities and agricultural areas, since stationarity in the quantity and quality of hydrologic resources cannot be assumed under climate and land use changes present in many parts of the U.S
Impacts of land-atmosphere interactions on regional convection and rainfall
Get PDFIn this dissertation, interactions between land-surface heterogeneities, land-atmosphere coupling, and moist convection and related mesoscale circulations were investigated in four major studies to improve and advance the understanding of high-resolution model simulations of regional convection and precipitation. A number of short-term (i.e., 24-48 hours) retrospective numerical experiments were conducted over a variety of land-atmosphere coupling hotspot regions across the globe. First, impacts of heterogeneous land surface on turbulent flow and mesoscale simulations were assessed. Experiments were conducted using the Weather Research and Forecasting (WRF) model coupled with a simple (slab) land surface model (LSM), a modestly complex Noah LSM, and a land data assimilation system (LDAS) with detailed surface fields. Three heterogeneity length scales: 1, 3, and 9 km, were employed to alter land cover and land use. The response of high-resolution model simulations’ to spatial scales changes of land-surface heterogeneity by modification of land-surface properties and changes in land-surface representation were investigated. Results indicate that both land-surface parameterizations and surface heterogeneity affect model simulations, and the impact of land-surface parameterizations is found to be more important, particularly for low frequency (f \u3c 10−4 hz) eddies and mesoscale circulations. Replacing a simple slab land model with more detailed land surface models (LSMs) (e.g., Noah or High-Resolution Land Data Assimilation System) can help reduce uncertainties in the simulation of surface fluxes which may be greatly affected by land-surface heterogeneity via improved turbulent characteristics over heterogeneous landscapes. An important result that emerges from the analysis is that the impact of land-surface heterogeneity on atmospheric feedbacks can be detected in mesoscale circulations that are roughly four times the heterogeneity spatial scale. It follows that the heterogeneity length scale that can influence mesoscale circulations would be a function of grid spacing in the model. Second, the role of land-atmosphere coupling over regions with relatively strong coupling between land-surface conditions and moist convection were assessed. The need for adopting a dynamic coupling strength within the land surface model was assessed by analyzing rainfall events and impacts of land-atmosphere coupling using the Noah land model and WRF model simulations over the U.S. southern Great Plains (SGP), Europe, northern India, and West Africa. Land-atmosphere coupling strength impacts on model parameterizations (i.e., land surface processes, PBL dynamics, and moist convection) were quantified and the range of regional variation in the coupling coefficient for model simulations was documented. Results indicate that the adoption of a dynamic land-atmosphere coupling formulation helps improve the simulation of surface fluxes and the resulting atmospheric state, thus dynamic coupling shows promise in modulating model results and improving convective system simulation and precipitation forecasts. For the four regions, the surface coupling coefficient does not affect the general location but could improve the intensity of simulated precipitation. Results highlight that there is high uncertainty in land-atmosphere coupling and the results from this and prior studies need to be considered with caution. In particular, zones identified as coupling hotspots in climate studies and their coupling strength would likely change depending on the model formulations and coupling coefficient assigned. Third, impacts of an updated convection scheme on high-resolution precipitation forecasts were assessed. At high resolution spatial scales, precipitation biases and errors can occur due to uncertainties in initial meteorological conditions, grid-scale cloud microphysics schemes, and/or subgrid-scale convection schemes. To reduce precipitation biases and uncertainties, scale-aware parameterized cloud dynamics were introduced to high-resolution forecasts by making several changes to the Kain-Fritsch (KF) convection parameterization scheme (CPS) in the WRF model. These changes include subgrid-scale cloud radiation interactions, a convective adjustment timescale, the cloud updraft mass flux impacting grid-scale vertical velocity, and a LCL-based methodology for parameterizing entrainment. This updated KF (UKF) CPS allows the convection scheme to facilitate a smooth transition from parameterized cloud physics to resolved grid-scale cloud physics across different grid resolutions. Results indicate that (1) high-resolution precipitation forecasting is more sensitive to the source of initial conditions than to grid-scale microphysics or convective parameterizations, and (2) the UKF CPS greatly alleviates excessive precipitation at 9 km grid spacing and improves results at 3 km grid spacing as well. In the last part of this dissertation, impacts of land-atmosphere-convection interactions on regional precipitation intensity and variation in the WRF model were assessed. Sensitivity experiments including effects of LSM, land-atmosphere coupling strength, and CPS on the fields of precipitation, surface scalars, and convection reveal that including a more detailed land surface parameterization, a dynamical surface coupling strength coefficient, and UKF CPS together, improves mesoscale simulations of several meteorological and convection parameters in the short-term high-resolution WRF model, increasing accuracy about 40% for precipitation intensity forecasts. (Abstract shortened by UMI.
Estimating environmental exposure of emerging agricultural contaminants using spatial data analysis and geographic information system
No full textAgricultural activities generate a wide range of potential contaminants that can degrade the quality of both surface and ground water, resulting in significant public health and environmental impacts. Amongst potential contaminants connected with farming, livestock antibiotics and hormones and soybean rust fungicides have only recently emerged as concerns. The use of antibiotics and hormones as growth promoters and anti-bacterial agents in the feed of most livestock, and the use of fungicides to control soybean rust are believed to play a leading role in the release of these substances into the environment. While livestock antibiotics/hormones are increasingly being found in water bodies, and have already been observed to cause extreme biological responses at low (ng/l) concentrations, fungicides are more of a future threat in states such as Indiana as they will likely be used to control soybean rust (a potentially devastating disease for soybeans in US) and may reach water resources and impact off target species such as fish and humans. Therefore, it is essential to assess the possible environmental impacts of these potential contaminants and identify areas that are most vulnerable to contamination. This study focuses on developing and applying modeling techniques to estimate the potential magnitude and spatial patterns of water resources contamination by these emerging agricultural contaminants. This was achieved by developing a mathematical screening tool as a first step to estimate the possibility of contamination of shallow groundwater. Model results for the State of Indiana demonstrate that transport rates and paths are highly sensitive to soil patterns and characteristics, and illustrate how this approach can be used to create spatial maps of leached fractions beyond a control plane. This was followed by a statewide risk assessment of both livestock antibiotics/hormones and the soybean rust fungicides. Assessment results indicate the regions in Indiana that are vulnerable to contamination by these two groups of compounds. The outputs of this study demonstrate the scale of the potential risk posed by these emerging contaminants and also establish a framework for developing comprehensive management and mitigation plans
Deforestation of cloud forest in the Central Highlands of Guatemala: Soil erosion and sustainability implications for Q\u27eqchi\u27 Maya communities
Get PDFUnderstanding the nexus between deforestation, food production, land degradation, and culture contributes knowledge that is useful for development practitioners working to enhance conservation and food security. Documenting deforestation and soil erosion in the Sierra Yalijux and Sierra Sacranix in the Central Highlands of Guatemala adds new knowledge about the rates and dynamics of deforestation and land degradation in areas with unique and sensitive cloud forest ecosystems. It also suggests possible areas of emphasis for efforts targeted at combining cloud forest conservation with sustainability for indigenous Q\u27eqchi\u27 communities. In addition, this work contributes to a small but growing body of literature concerned with human-environment interactions in cloud forests, and demonstrates how a transdisciplinary approach can be used to investigate these interactions. The cloud forest in the Sierra Yalijux and Sierra Sacranix in the Central Highlands of Guatemala is largely unprotected and provides habitat for a wide variety of wildlife and critical ecosystem services for rural communities. A mix of research methods was used to investigate the human-environment interactions between the cloud forest and the Q\u27eqchi\u27 people living in the vicinity, and implications for sustainability. Deforestation patterns and rates for the cloud forest, and impacts on soil erosion, were examined using land use change mapping from remote sensing imagery (Landsat TM, high-resolution digital orthophotos, and digital elevation models) and soil erosion modeling using the Revised Universal Soil Loss Equation. Contributing factors to deforestation, as well as implications for sustainability of food production and ecosystem services in Q\u27eqchi\u27 communities were investigated using analysis of quantitative and qualitative data from surveys and focus groups in several communities. Annual deforestation rates were highest in the Sierra Yalijux study area, nearly doubling from 0.65 percent/year between 1986 and 1996 to 1.19 percent/year between 1996 and 2006. In the Sierra Sacranix, the annual deforestation rate increased from approximately 0.25 percent/year to 0.81 percent/year, more than tripling between 1986 and 2006. Population increase in Q\u27eqchi\u27 communities is driving land subdivision, which is leading to reduced fallow periods on land already cleared for subsistence farming, and is ultimately leading to increased clearing of cloud forest. Thus deforestation has been caused by expansion of subsistence agriculture in response to increased food demand and increased pressure on land resources, such as soils. Farmers have been gradually clearing cloud forest on increasingly steep slopes in order to cultivate enough land to meet growing food needs. The implications of cloud forest loss are significant for Q\u27eqchi\u27 communities. Farmers rely on the cloud forest for ecosystem services such as organic matter input to enhance soil fertility, potable water availability, and microclimate stability. The Q\u27eqchi\u27 have observed reductions in the input of leaf matter to their agricultural plots, changes in the precipitation regime, and decreased availability of potable water from springs in recent decades, all of which are associated with cloud forest removal. Estimates of soil erosion rates from model calculations show that soil loss is most severe in agricultural areas. Expansion of agriculture was observed in both catchments, and as a result soil loss rates have increased. However the increase of soil loss as a result of deforestation was relatively small compared to the overall contribution from agricultural areas. Simulation results comparing current practices to a soil conservation scenario indicate that support practices such as bench terracing and polyculture would significantly mitigate the most severe soil erosion. These measures accomplish this by reducing slope (terracing) and increasing vegetation cover (polyculture). We anticipate that reducing soil loss through support practices would likely increase soil fertility in the long-term and increase nutrition in Q\u27eqchi\u27 communities through the consumption of a wider variety of crops, which would enhance food security. Reducing the decline of soil fertility in the long run and increasing agricultural intensity through polyculture would also curb pressure on the cloud forest, even as population continues to increase in the region
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